contributor author | Da Hu | |
contributor author | Long Chen | |
contributor author | Jing Du | |
contributor author | Jiannan Cai | |
contributor author | Shuai Li | |
date accessioned | 2022-08-18T12:11:52Z | |
date available | 2022-08-18T12:11:52Z | |
date issued | 2022/06/29 | |
identifier other | %28ASCE%29CP.1943-5487.0001038.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4286182 | |
description abstract | First responders often lack information and visual clues regarding interior spaces in disaster rubble, preventing efficient, effective, and safe search and rescue for victims trapped in collapsed structures. Rapidly detecting and acquiring information about the voids in collapsed structures that could contain surviving victims is critical for urban search and rescue. However, reconstructing the buried voids in three dimensions (3D) and communicating the relevant information such as buried depth and void size to first responders remain significant challenges. In response, this study proposes a see-through technique by integrating ground-penetrating radar (GPR) with interactive augmented reality (AR). The contribution of this study is twofold. First, a new method is developed to process collected GPR data to reconstruct potential voids in disaster rubble in 3D and extract the buried depth and void size from the GPR data. The coordinates of void boundaries are extracted from multiple GPR scans to generate sparse point clouds. An improved alpha-shape method is exploited to reconstruct the 3D space beneath disaster rubble from the point clouds. Second, an interactive augmented reality interface is developed to enable first responders to visualize the voids in collapsed structures in 3D together with relevant information to assist urban search and rescue. The results from simulations and pilot experiments demonstrate the feasibility and potential of the proposed methods. | |
publisher | ASCE | |
title | Seeing through Disaster Rubble in 3D with Ground-Penetrating Radar and Interactive Augmented Reality for Urban Search and Rescue | |
type | Journal Article | |
journal volume | 36 | |
journal issue | 5 | |
journal title | Journal of Computing in Civil Engineering | |
identifier doi | 10.1061/(ASCE)CP.1943-5487.0001038 | |
journal fristpage | 04022021 | |
journal lastpage | 04022021-17 | |
page | 17 | |
tree | Journal of Computing in Civil Engineering:;2022:;Volume ( 036 ):;issue: 005 | |
contenttype | Fulltext | |